In imaging methods in medicine, for creating each pixel of a recorded image, the method mostly relies on evaluating a measured value that has been recorded in a specific time interval. Thus for example Computed Tomography (“CT”) detects the local x-ray attenuation of the body structure of the patient integrated over the recording time. In this case the recording time mostly lies in the order of magnitude of 1 second.
Because of the integration of the measurement signals over the recording time, the motion of objects, which as rule represent organs of a human or animal patient, is a serious problem in medical imaging. As a rule, in medical images that record an image of an object moving during the recording there are always motion artifacts in the area of the recorded object. For example during a recording of the heart with a CT or other recording method, its motion leads to difficulties in the imaging resolution of structures, e.g. of the coronary arteries located on this heart.
This problem can be countered with a simple shortening of the recording time, but as a rule this has a disadvantageous effect on the signal-to-noise ratio or, with an increase in the intensity related to this, on the radiation load (with a CT or corresponding recording method) or the load caused by a variable magnetic field (e.g. for recordings made by a Magnetic Resonance Tomograph MRT).
As well as technical solutions such as e.g. faster rotation times and dual-source CT technology for optimizing the time resolution, a plurality of software-based solutions have been developed in recent years.
Within the very broad field of motion-compensated reconstruction of recordings of the heart, a frequent common factor is the explicit determination of 4D vector fields, which describe the spatial and temporal course of the heart motion, in order to then employ these subsequently within the framework of a motion-compensating reconstruction. Differences between the known methods primarily lie in whether 4D fields are to be determined directly from multiphase reconstructions or whether these are implicitly included in the reconstruction as free parameters within the framework of a minimization method with the aid of a suitable target metric, e.g. with methods such as SnapShot Freeze, Motion Artifact Metric method (MAM) or Motion Compensation based on Partial Angle Reconstructions (PAMoCo).
A common element in these methods is that a heavy local restriction of the correction for limiting the degrees of freedom is needed, wherein frequently the regions of the coronary arteries that have been obtained by way of segmentation from a standard reconstruction are selected. As an alternative thereto there are also approaches that model the motion of the complete heart muscle.